{"created":"2025-01-18T23:40:19.084504+00:00","updated":"2025-01-21T15:48:29.738612+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00090894","sets":["1164:4619:6988:7113"]},"path":["7113"],"owner":"11","recid":"90894","title":["精度の高い楕円限定当てはめ"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-03-07"},"_buckets":{"deposit":"797522af-52b7-4ba1-8101-4a0c2ac50836"},"_deposit":{"id":"90894","pid":{"type":"depid","value":"90894","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"精度の高い楕円限定当てはめ","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"精度の高い楕円限定当てはめ"},{"subitem_title":"High Accuracy Ellipse-Specific Fitting","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2013-03-07","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"豊橋技術科学大学情報・知能工学系"},{"subitem_text_value":"豊橋技術科学大学情報・知能工学系"},{"subitem_text_value":"岡山大学大学院自然科学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Computer Science and Engineering, Toyohashi University of Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science and Engineering, Toyohashi University of Technology","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science, Okayama University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/90894/files/IPSJ-CVIM13186014.pdf"},"date":[{"dateType":"Available","dateValue":"2015-03-07"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM13186014.pdf","filesize":[{"value":"1.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"9bdddac8-cb90-446a-b00a-05f548ba102d","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2013 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"益崎, 智成"},{"creatorName":"菅谷, 保之"},{"creatorName":"金谷, 健一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tomonari, Masuzaki","creatorNameLang":"en"},{"creatorName":"Yasuyuki, Sugaya","creatorNameLang":"en"},{"creatorName":"Kenichi, Kanatani","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本論文では画像から抽出した点列に常に楕円が当てはまる新しい方法を提案する．現時点で最も優れた楕円当てはめ法は金谷らの超精度くりこみ法であるが，ノイズが非常に大きいとき双曲線が当てはまることがある．提案手法はそのような場合にデータ点のランダムサンプリングによって点列に最も近い楕円を選ぶ．これまでに楕円のみを当てはめる方法としてFitzgibbonらの方法，およびSzpakらの方法が提案されているが，シミュレーション実験によって提案手法はそれらより精度が高いことを示す．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We propose a new method that always fits an ellipse to a point sequence extracted from images. The currently known best method is hyper-renormalization of Kanatani et al., but it may return a hyperbola when the noise in the data is very large. Our proposed method returns an ellipse close to the point sequence by random sampling of data points. Doing simulation, we show that our method has higher accuracy than the method of Fitzgibbon et al. and the method of Szpak et al., the two methods so far proposed to always return an ellipse.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2013-03-07","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"14","bibliographicVolumeNumber":"2013-CVIM-186"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":90894,"links":{}}